JDBC

JDBC source connector

Description

Read external data source data through JDBC.

:::tip

Warn: for license compliance, you have to provide database driver yourself, copy to $SEATNUNNEL_HOME/lib/ directory in order to make them work.

e.g. If you use MySQL, should download and copy mysql-connector-java-xxx.jar to $SEATNUNNEL_HOME/lib/. For Spark/Flink, you should also copy it to $SPARK_HOME/jars/ or $FLINK_HOME/lib/.

:::

Key features

• batch
• stream
• exactly-once
• column projection

supports query SQL and can achieve projection effect.

• parallelism
• support user-defined split
• support multiple table read

Options

driver [string]

The jdbc class name used to connect to the remote data source, if you use MySQL the value is com.mysql.cj.jdbc.Driver.

user [string]

userName

password [string]

password

url [string]

The URL of the JDBC connection. Refer to a case: jdbc:postgresql://localhost/test

query [string]

Query statement

compatible_mode [string]

The compatible mode of database, required when the database supports multiple compatible modes. For example, when using OceanBase database, you need to set it to 'mysql' or 'oracle'.

connection_check_timeout_sec [int]

The time in seconds to wait for the database operation used to validate the connection to complete.

partition_column [string]

The column name for parallelism's partition, only support numeric type.

partition_upper_bound [BigDecimal]

The partition_column max value for scan, if not set SeaTunnel will query database get max value.

partition_lower_bound [BigDecimal]

The partition_column min value for scan, if not set SeaTunnel will query database get min value.

partition_num [int]

The number of partition count, only support positive integer. default value is job parallelism

fetch_size [int]

For queries that return a large number of objects, you can configure the row fetch size used in the query to improve performance by reducing the number database hits required to satisfy the selection criteria. Zero means use jdbc default value.

properties

Additional connection configuration parameters,when properties and URL have the same parameters, the priority is determined by the
specific implementation of the driver. For example, in MySQL, properties take precedence over the URL.

table_path

The path to the full path of table, you can use this configuration instead of query.

examples:

• mysql: "testdb.table1"
• oracle: "test_schema.table1"
• sqlserver: "testdb.test_schema.table1"
• postgresql: "testdb.test_schema.table1"

table_list

The list of tables to be read, you can use this configuration instead of table_path

example

table_list = [
  {
    table_path = "testdb.table1"
  }
  {
    table_path = "testdb.table2"
    query = "select * from testdb.table2 where id > 100"
  }
]

where_condition

Common row filter conditions for all tables/queries, must start with where. for example where id > 100

split.size

The split size (number of rows) of table, captured tables are split into multiple splits when read of table.

split.even-distribution.factor.lower-bound

The lower bound of the chunk key distribution factor. This factor is used to determine whether the table data is evenly distributed. If the distribution factor is calculated to be greater than or equal to this lower bound (i.e., (MAX(id) - MIN(id) + 1) / row count), the table chunks would be optimized for even distribution. Otherwise, if the distribution factor is less, the table will be considered as unevenly distributed and the sampling-based sharding strategy will be used if the estimated shard count exceeds the value specified by sample-sharding.threshold. The default value is 0.05.

split.even-distribution.factor.upper-bound

The upper bound of the chunk key distribution factor. This factor is used to determine whether the table data is evenly distributed. If the distribution factor is calculated to be less than or equal to this upper bound (i.e., (MAX(id) - MIN(id) + 1) / row count), the table chunks would be optimized for even distribution. Otherwise, if the distribution factor is greater, the table will be considered as unevenly distributed and the sampling-based sharding strategy will be used if the estimated shard count exceeds the value specified by sample-sharding.threshold. The default value is 100.0.

split.sample-sharding.threshold

This configuration specifies the threshold of estimated shard count to trigger the sample sharding strategy. When the distribution factor is outside the bounds specified by chunk-key.even-distribution.factor.upper-bound and chunk-key.even-distribution.factor.lower-bound, and the estimated shard count (calculated as approximate row count / chunk size) exceeds this threshold, the sample sharding strategy will be used. This can help to handle large datasets more efficiently. The default value is 1000 shards.

split.inverse-sampling.rate

The inverse of the sampling rate used in the sample sharding strategy. For example, if this value is set to 1000, it means a 1/1000 sampling rate is applied during the sampling process. This option provides flexibility in controlling the granularity of the sampling, thus affecting the final number of shards. It's especially useful when dealing with very large datasets where a lower sampling rate is preferred. The default value is 1000.

common options

Source plugin common parameters, please refer to Source Common Options for details.

tips

If partition_column is not set, it will run in single concurrency, and if partition_column is set, it will be executed in parallel according to the concurrency of tasks.

appendix

there are some reference value for params above.

datasource	driver	url	maven
mysql	com.mysql.cj.jdbc.Driver	jdbc:mysql://localhost:3306/test	https://mvnrepository.com/artifact/mysql/mysql-connector-java
postgresql	org.postgresql.Driver	jdbc:postgresql://localhost:5432/postgres	https://mvnrepository.com/artifact/org.postgresql/postgresql
dm	dm.jdbc.driver.DmDriver	jdbc:dm://localhost:5236	https://mvnrepository.com/artifact/com.dameng/DmJdbcDriver18
phoenix	org.apache.phoenix.queryserver.client.Driver	jdbc:phoenix:thin:url=http://localhost:8765;serialization=PROTOBUF	https://mvnrepository.com/artifact/com.aliyun.phoenix/ali-phoenix-shaded-thin-client
sqlserver	com.microsoft.sqlserver.jdbc.SQLServerDriver	jdbc:sqlserver://localhost:1433	https://mvnrepository.com/artifact/com.microsoft.sqlserver/mssql-jdbc
oracle	oracle.jdbc.OracleDriver	jdbc:oracle:thin:@localhost:1521/xepdb1	https://mvnrepository.com/artifact/com.oracle.database.jdbc/ojdbc8
sqlite	org.sqlite.JDBC	jdbc:sqlite:test.db	https://mvnrepository.com/artifact/org.xerial/sqlite-jdbc
gbase8a	com.gbase.jdbc.Driver	jdbc:gbase://e2e_gbase8aDb:5258/test	https://www.gbase8.cn/wp-content/uploads/2020/10/gbase-connector-java-8.3.81.53-build55.5.7-bin_min_mix.jar
starrocks	com.mysql.cj.jdbc.Driver	jdbc:mysql://localhost:3306/test	https://mvnrepository.com/artifact/mysql/mysql-connector-java
db2	com.ibm.db2.jcc.DB2Driver	jdbc:db2://localhost:50000/testdb	https://mvnrepository.com/artifact/com.ibm.db2.jcc/db2jcc/db2jcc4
tablestore	com.alicloud.openservices.tablestore.jdbc.OTSDriver	"jdbc:ots:http s://myinstance.cn-hangzhou.ots.aliyuncs.com/myinstance"	https://mvnrepository.com/artifact/com.aliyun.openservices/tablestore-jdbc
saphana	com.sap.db.jdbc.Driver	jdbc:sap://localhost:39015	https://mvnrepository.com/artifact/com.sap.cloud.db.jdbc/ngdbc
doris	com.mysql.cj.jdbc.Driver	jdbc:mysql://localhost:3306/test	https://mvnrepository.com/artifact/mysql/mysql-connector-java
teradata	com.teradata.jdbc.TeraDriver	jdbc:teradata://localhost/DBS_PORT=1025,DATABASE=test	https://mvnrepository.com/artifact/com.teradata.jdbc/terajdbc
Snowflake	net.snowflake.client.jdbc.SnowflakeDriver	jdbc//<account_name>.snowflakecomputing.com	https://mvnrepository.com/artifact/net.snowflake/snowflake-jdbc
Redshift	com.amazon.redshift.jdbc42.Driver	jdbc:redshift://localhost:5439/testdb?defaultRowFetchSize=1000	https://mvnrepository.com/artifact/com.amazon.redshift/redshift-jdbc42
Vertica	com.vertica.jdbc.Driver	jdbc:vertica://localhost:5433	https://repo1.maven.org/maven2/com/vertica/jdbc/vertica-jdbc/12.0.3-0/vertica-jdbc-12.0.3-0.jar
Kingbase	com.kingbase8.Driver	jdbc:kingbase8://localhost:54321/db_test	https://repo1.maven.org/maven2/cn/com/kingbase/kingbase8/8.6.0/kingbase8-8.6.0.jar
OceanBase	com.oceanbase.jdbc.Driver	jdbc:oceanbase://localhost:2881	https://repo1.maven.org/maven2/com/oceanbase/oceanbase-client/2.4.3/oceanbase-client-2.4.3.jar
Hive	org.apache.hive.jdbc.HiveDriver	jdbc:hive2://localhost:10000	https://repo1.maven.org/maven2/org/apache/hive/hive-jdbc/3.1.3/hive-jdbc-3.1.3-standalone.jar

Example

simple:

Jdbc {
    url = "jdbc:mysql://localhost/test?serverTimezone=GMT%2b8"
    driver = "com.mysql.cj.jdbc.Driver"
    connection_check_timeout_sec = 100
    user = "root"
    password = "123456"
    query = "select * from type_bin"
}

parallel:

env {
  execution.parallelism = 10
  job.mode = "BATCH"
}
source {
    Jdbc {
        url = "jdbc:mysql://localhost/test?serverTimezone=GMT%2b8"
        driver = "com.mysql.cj.jdbc.Driver"
        connection_check_timeout_sec = 100
        user = "root"
        password = "123456"
        query = "select * from type_bin"
        partition_column = "id"
        partition_num = 10
        # Read start boundary
        #partition_lower_bound = ...
        # Read end boundary
        #partition_upper_bound = ...
    }
}

sink {
  Console {}
}

Using table_path read:

Configuring table_path will turn on auto split, you can configure split.* to adjust the split strategy

Jdbc {
    url = "jdbc:mysql://localhost/test?serverTimezone=GMT%2b8"
    driver = "com.mysql.cj.jdbc.Driver"
    connection_check_timeout_sec = 100
    user = "root"
    password = "123456"
  
    # e.g. table_path = "testdb.table1"、table_path = "test_schema.table1"、table_path = "testdb.test_schema.table1"
    table_path = "testdb.table1"
    #split.size = 8096
    #split.even-distribution.factor.upper-bound = 100
    #split.even-distribution.factor.lower-bound = 0.05
    #split.sample-sharding.threshold = 1000
    #split.inverse-sampling.rate = 1000
}

multiple table read:

Configuring table_list will turn on auto split, you can configure split.* to adjust the split strategy

Jdbc {
    url = "jdbc:mysql://localhost/test?serverTimezone=GMT%2b8"
    driver = "com.mysql.cj.jdbc.Driver"
    connection_check_timeout_sec = 100
    user = "root"
    password = "123456"

    table_list = [
        {
          # e.g. table_path = "testdb.table1"、table_path = "test_schema.table1"、table_path = "testdb.test_schema.table1"
          table_path = "testdb.table1"
        },
        {
          table_path = "testdb.table2"
          # Use query filetr rows & columns
          query = "select id, name from testdb.table2 where id > 100"
        }
    ]
    #where_condition= "where id > 100"
    #split.size = 8096
    #split.even-distribution.factor.upper-bound = 100
    #split.even-distribution.factor.lower-bound = 0.05
    #split.sample-sharding.threshold = 1000
    #split.inverse-sampling.rate = 1000
}

Changelog

2.2.0-beta 2022-09-26

• Add ClickHouse Source Connector

2.3.0-beta 2022-10-20

• [Feature] Support Phoenix JDBC Source (2499)
• [Feature] Support SQL Server JDBC Source (2646)
• [Feature] Support Oracle JDBC Source (2550)
• [Feature] Support StarRocks JDBC Source (3060)
• [Feature] Support GBase8a JDBC Source (3026)
• [Feature] Support DB2 JDBC Source (2410)

next version

• [BugFix] Fix jdbc split bug (3220)
• [Feature] Support Sqlite JDBC Source (3089)
• [Feature] Support Tablestore Source (3309)
• [Feature] Support Teradata JDBC　Source (3362)
• [Feature] Support JDBC Fetch Size Config (3478)
• [Feature] Support Doris JDBC Source (3586)
• [Feature] Support Redshift JDBC Sink(#3615)
• [BugFix] Fix jdbc connection reset bug (3670)
• [Improve] Add Vertica connector(#4303)